Abstract
This paper presents an approach to modeling multi-expert decision systems. The proposed method is based on the idea of fuzzy linguistic label, which is suitable for analyzing real life decision-making process under uncertainty, where subjective criteria play an important role. A modified form of information system for modeling the action of a group of experts is introduced. The notions of dominating, boundary, and negative linguistic values are adopted. Furthermore, a novel definition of the fuzzy linguistic label, the measure of certainty of a linguistic label, and the compatibility function between elements of the universe and a linguistic label are given. Finally, a way of aggregating the experts’ knowledge for selecting a set of objects that best fit the preference of a decision-maker is proposed. Independent vectors of preference degrees for both the attributes and their linguistic values are applied. A simple illustrating example is provided, which presents an analysis of a decision process performed by three experts.
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Mieszkowicz-Rolka, A., Rolka, L. (2017). Fuzzy Linguistic Labels in Multi-expert Decision Making. In: Martín-Vide, C., Neruda, R., Vega-Rodríguez, M. (eds) Theory and Practice of Natural Computing. TPNC 2017. Lecture Notes in Computer Science(), vol 10687. Springer, Cham. https://doi.org/10.1007/978-3-319-71069-3_10
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DOI: https://doi.org/10.1007/978-3-319-71069-3_10
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